ASTR 7730 - Statistical and Computational Methods in Physics & Astronomy

This course will discuss a few widely applicable statistical and computational methods of analyzing and modeling phenomena in astrophysics, biophysics, and physics in general. The learning objective is to apply the methods learned in this course to connect experimental or observational data with underlying physical processes through numerical simulations and statistical analyses. Topics that will be covered in this course include stochastic process simulations, Monte Carlo methods, Bayesian analysis, and basic machine learning algorithms. This is a graduate-level course. The course will use Python as the programming language for demonstration and use many examples in physics and astronomy. Students are assumed to be comfortable in programming and have an introductory-level knowledge in physics.